Add prediction message

app.py

@@ -142,7 +142,7 @@ with demo:
     decrypt_button = gr.Button("Decrypt the output")
 
     prediction_output = gr.Textbox(
-        label="Credit card approval high risk: ", max_lines=1, interactive=False
+        label="Prediction", max_lines=1, interactive=False
     )
 
     # Button generate the keys

backend.py

@@ -419,6 +419,7 @@ def decrypt_output(client_id):
     output_proba = client.deserialize_decrypt_dequantize(encrypted_output_proba)
 
     # Determine the predicted class
-    output = numpy.argmax(output_proba, axis=1)
+    output = numpy.argmax(output_proba, axis=1).squeeze()
     
-    return output
+    # A "0" output means approving the credit card has low risk, while "1" is high risk
+    return "Credit card has been approved ✅" if output == 0 else "Credit card has been rejected ❌"

development.py

@@ -24,6 +24,14 @@ def get_processed_multi_inputs(data):
 
 print("Load and pre-process the data")
 
+# Original data set can be found here : 
+# https://www.kaggle.com/datasets/rikdifos/credit-card-approval-prediction/data
+# It then has been cleaned using the following notebook : 
+# https://www.kaggle.com/code/samuelcortinhas/credit-cards-data-cleaning
+# A few additional pre-processing steps has bee applied to this data set as well : 
+# - "ID" column has been removed 
+# - "Total_income" values have been multiplied by 0.14 to make its median value match France's 
+#   annual salary one from 2023 (in euros) 
 data = pandas.read_csv(DATA_PATH, encoding="utf-8")
 
 # Define input and target data